scholarly journals An advanced knowledge-based analysis of company vision statements

2022 ◽  
Author(s):  
Alexander Kaiser ◽  
Lisa-Maria Baumgartner ◽  
Anna Katharina Grill ◽  
Sebastian Neumaier
2006 ◽  
Vol 54 (4) ◽  
pp. 93-100
Author(s):  
E. Morel ◽  
B. Tartakovsky ◽  
S.R. Guiot ◽  
M. Perrier

Anaerobic digestion model no.1 (ADM1) was used for tuning and performance analysis of the multi-model observer based estimator (mmOBE). The mmOBE was based on the variable structure model (VSM) of the anaerobic digestion model, which consists of several local submodels, each of which describes a typical process state. Depending on the hydraulic retention time, ADM1 simulated the methanogenic, organic overload, and acidogenic states of the process. These simulations allowed for optimising tunable parameters of the mmOBE. Owing to relatively slow process dynamics, a data acquisition interval as large as one day was sufficient to obtain acceptable accuracy. The simulations of mmOBE performance showed excellent rate of mmOBE convergence to ADM1 outputs. Moreover, mmOBE successfully estimated key kinetic parameters, such as maximal transformation rates of CODs, VFAs, and methane. These estimations can be used in the development of the advanced knowledge-based process system, which uses both available measurements and estimations of key kinetic parameters for extended diagnosis of failures and process trend analysis.


Author(s):  
Jill Shepherd

While there are many useful ways of describing and discussing the Digital Era, explanations of its existence are lacking. The Digital Era is characterized by technology which increases the speed and breadth of knowledge turnover within the economy and society. Evolutionary theory, as an explanation of the system we live in, states that sustainability relies on knowledge turnover. In parts of the system which are relatively stable, knowledge turnover is low, and new variation, when produced, is rarely retained. In other, less stable parts of the system, faster knowledge turnover is advantageous as new knowledge is produced more frequently allowing for adaptation to the changing surrounding environment. Mixing and matching rates of knowledge turnover makes for a dynamic but ever-lasting world. The Digital Era can be seen as the development of an evolutionary system in which knowledge turnover is not only very high, but also increasingly out of the control of humans, making it a time in which our lives become more difficult to manage. For example, in the second generation Internet, ‘the semantic web’, functionality, which understands meaning, replaces the search function of unknowingly matching words, which often have multiple meanings. In time, within this version of the Internet, software agents will exchange knowledge without human intervention. Equally, our understanding of the knowledge embedded within the human genome about how we relate to the world, generated in association with technology and freely available on the Internet, raises questions about our assumptions of control. Do we know enough about our future to change our genome? Can we control such changes and their diffusion? The social and economic implications of the Digital Era are huge and will increase as technological functionality becomes more knowledge-based, our everyday lives and understanding of ourselves become more linked to it, and it takes on a ‘life’ of its own. Understanding the Digital Era in terms of evolution will help ensure we build sustainable socio-economic relationships both with technology and with the advanced knowledge that technology helps us create.


2003 ◽  
Vol 13 (1) ◽  
pp. 39-46 ◽  
Author(s):  
Bratislav Milovanovic ◽  
Vera Markovic ◽  
Zlatica Marinkovic ◽  
Zoran Stankovic

This paper presents some applications of neural networks in the microwave modeling. The applications are related to modeling of either passive or active structures and devices. Modeling is performed using not only simple multilayer perception network (MLP) but also advanced knowledge based neural network (KBNN) structures.


2015 ◽  
Vol 1 (1) ◽  
pp. 215-225 ◽  
Author(s):  
Ioan G. Pop ◽  
Mihai-Florin Talpos ◽  
Igor Prisac

AbstractThe paper presents a new, transdisciplinary approach on the DIKW (Data, Information, Knowledge, and Wisdom) hierarchy, offering arguments that the hierarchy is unsound and even methodologically undesirable. The purpose of the paper is to identify a new and more complete perspective on knowledge integration. This model is based on another scale, in a synergistic-generative transdisciplinary manner, in order to transfer and implement knowledge in the knowledge based society/economy context. The new knowledge pattern, named DIMLAK (Data, Information, Messages, Learning, and Advanced Knowledge) is reconfigured to explain the way the advanced knowledge is achieved as a top level of the transdisciplinary integrated and integrative knowledge system. The proposed model is working complementarily as breadth through depth approach, opening a new vision in the knowledge achieving process.


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